Software-defined vehicles are no longer theoretical. They are already on the road; running increasingly complex software stacks that manage safety systems, autonomy features, diagnostics, infotainment and user experiences. However, as vehicles evolve there advanced features depend heavily continuous cloud connectivity. mimik solves fundamental constraint by delivering in-vehicle intelligence that can run locally in the vehicle, while remaining seamlessly connected to a central cloud if needed. Its SOAFee Blueprint Architecture runs intelligent, offline-capable AI agents in-vehicle without restructuring the existing hardware stack.

From Cloud-First to Vehicle-First Intelligence

mimik’s platform underpins software-defined-vehicle (SDV) features such as hyper-personalization, real-time decision making, predictive maintenance, usage-based insurance and context-aware infotainment by processing data at the edge or in the vehicle. mimik’s approach aligns with SOAFEE’s vision by shifting intelligence into the vehicle itself, while maintaining interoperability with cloud services when available. The result is a hybrid execution model where services, APIs, and AI workloads operate locally by default and extend outward only when connectivity allows.

This architectural shift enables vehicles to function as autonomous, resilient computing environments, rather than thin clients tethered to the cloud.

mim OE: The Agentix-Native Runtime Inside the Vehicle

At the core of mimik’s SOAFEE Blueprint implementation is mim OE, mimik’s Agentix-Native execution layer. mim OE gives automakers a continuous cloud-native runtime across vehicle computing devices, letting them develop, deploy and manage workloads like microservices and AI agents directly inside the vehicle. AI-native access to vehicle functions in the SOAFEE blueprint, are exposed as callable tools for AI agents, letting agentic apps compose and adapt vehicle behaviours dynamically at the edge.

Unlike traditional runtimes, mim OE is designed for distributed intelligence:

• Services and AI agents run locally, not remotely
• Nodes discover each other dynamically
• Interactions continue safely even when disconnected

Making SOAFEE Operational—Without Re-Architecture

SOAFEE defines how automotive software should be structured and deployed. mim OE makes that structure operational in real-world vehicles.

With mim OE, SOAFEE-aligned workloads can be introduced in two complementary ways:

1. Native microservices implementing new functionality
2. Proxy agents that expose existing legacy systems as APIs

This dual model removes the need for a “rip-and-replace” strategy. Legacy investments remain intact while new capabilities are layered on top, allowing OEMs to modernize at their own pace.

Extending SOAFEE into the AI Domain with MCP

As vehicles incorporate more AI-driven behavior, exposing services alone is no longer sufficient. AI systems need a structured way to discover, negotiate, and consume vehicle capabilities. mimik addresses this by integrating the Model Context Protocol (MCP) into its SOAFEE Blueprint implementation. SOAFEE standardizes what vehicle services are available and MCP defines how AI agents interact with those services.

Blueprint in Action: A Practical Example

In a SOAFEE-aligned vehicle running mixed operating systems (QNX, Linux, Android), mim OE enables:

• In-vehicle services (e.g., comfort controls, access management) to run as microservices
• Secure key management via agent-based access control
• Driver smartphones to act as temporary service aggregators
• Seamless bridging between automotive and non-automotive environments

The vehicle effectively becomes a super-gateway, connecting embedded automotive systems with AI-enabled consumer devices—without sacrificing safety or reliability.

Why This Matters for OEMs and Tier 1s

mimik’s SOAFEE Blueprint implementation delivers tangible advantages:

• Standards alignment without vendor lock-in
• Offline-first operation for safety-critical systems
• Incremental adoption that protects existing investments
• AI readiness through MCP-enabled agent interaction
• Future scalability across evolving hardware and software stacks

Rather than choosing between compliance and innovation, OEMs gain both.

Watch the Technical Walkthrough

To see the SOAFEE Blueprint with mim OE and MCP in action, watch the full technical walkthrough below.

Moving Forward with SOAFEE and mimik

mimik continues to collaborate with the SOAFEE community to advance practical, deployable architectures for software-defined vehicles.

Opportunities include:

• Proof-of-concept programs
• Integration pilots
• Joint Blueprint evolution

Whether you are building next-generation vehicle platforms or extending existing ones, mimik provides a path to resilient, AI-native, in-vehicle intelligence—aligned with SOAFEE standards and designed for real-world conditions.

The post mimik Brings In-Vehicle API, AI Inference and MCP Gateway to SOAFEE Blueprint Architecture first appeared on mimik.

Modern multi-agent systems ranging from sensor networks monitoring critical infrastructure to crowdsourcing platforms aggregating human intelligence can suffer significant performance degradation due to systematic biases that vary with environmental conditions. Current approaches either ignore these biases, leading to suboptimal decisions, or require expensive calibration procedures that are often infeasible in practice. This performance gap has real consequences: inaccurate environmental monitoring, unreliable financial predictions, and flawed aggregation of human judgments. This paper addresses the fundamental question: when can we learn and correct for these unknown biases to recover near-optimal performance, and when is such learning futile? We develop a theoretical framework that decomposes biases into learnable systematic components and irreducible stochastic components, introducing the concept of learnability ratio as the fraction of bias variance predictable from observable covariates. This ratio determines whether bias learning is worthwhile for a given system. We prove that the achievable performance improvement is fundamentally bounded by this learnability ratio, providing system designers with quantitative guidance on when to invest in bias learning versus simpler approaches. We present the Adaptive Bias Learning and Optimal Combining (ABLOC) algorithm, which iteratively learns bias-correcting transformations while optimizing combination weights through closedform solutions, guaranteeing convergence to these theoretical bounds. Experimental validation demonstrates that systems with high learnability ratios can recover significant performance (we achieved 40%-70% of theoretical maximum improvement in our examples), while those with low learnability show minimal benefit, validating our diagnostic criteria for practical deployment decisions.

Published on Arxiv

The post Optimal Information Combining for Multi-Agent Systems Using Adaptive Bias Learning first appeared on mimik.

This study introduces Device First Continuum AI (DFC-AI), a transformative architecture within the Hybrid Edge Cloud paradigm designed to address the limitations of traditional cloud-centric artificial intelligence across diverse applications. DFC-AI prioritizes the deployment of intelligent agents, built on a microservices framework, that originates and primarily resides on end devices, extending to gateways and cloud servers as needed. This Device-First approach is essential for enabling real-time decision-making and personalized experiences for both industrial and consumer applications, particularly in scenarios demanding low latency, operation in disconnected environments, and efficient management of massive data streams. The study highlights the fundamental challenges of relying solely on centralized cloud or basic edge computing models, including prohibitive bandwidth costs, energy inefficiency, and compromised user privacy. By embedding intelligence at the device level, DFC-AI overcomes these limitations, fostering autonomous operation, seamless collaboration among devices, and substantial reductions in operational overhead, moving us closer to realizing the potential of truly human-like artificial intelligence in machines. Through illustrative examples spanning various sectors, this study demonstrates the potential of DFC-AI to unlock a new era of holistic, responsive, and user-centric intelligent systems, paving the way for innovative applications and enhanced digital experiences in an increasingly connected world.

The post Device First Continuum AI (DFC-AI): Realizing Human-Like AI first appeared on mimik.

Industrial automation in the energy sector requires AI systems that can operate autonomously regardless of network availability, a requirement that cloud-centric architectures cannot meet. This paper evaluates the application of Device-First Continuum AI (DFC-AI) to critical energy sector operations. DFC-AI, a specialized architecture within the Hybrid Edge Cloud paradigm, implements intelligent agents using a microservices architecture that originates at end devices and extends across the computational continuum. Through comprehensive simulations of energy sector scenarios including drone inspections, sensor networks, and worker safety systems, we demonstrate that DFC-AI maintains full operational capability during network outages while cloud and gateway-based systems experience complete or partial failure. Our analysis reveals that zero-configuration GPU discovery and heterogeneous device clustering are particularly well-suited for energy sector deployments, where specialized nodes can handle intensive AI workloads for entire fleets of inspection drones or sensor networks. The evaluation shows that DFC-AI achieves significant latency reduction and energy savings compared to cloud architectures. Additionally, we find that gateway based edge solutions can paradoxically cost more than cloud solutions for certain energy sector workloads due to infrastructure overhead, while DFC-AI can consistently provide cost savings by leveraging enterprise-owned devices. These findings, validated through rigorous statistical analysis, establish that DFC-AI addresses the unique challenges of energy sector operations, ensuring intelligent agents remain available and functional in remote oil fields, offshore platforms, and other challenging environments characteristic of the industry.

Published on Arxiv

The post Evaluating Device-First Continuum AI (DFC-AI) for Autonomous Operations in the Energy Sector first appeared on mimik.

Make AWS Spot Instances Operationally Impactful for AI and Mission-Critical Workloads with mimik

Most enterprises love the 90% savings AWS Spot Instances deliver but hesitate to trust Spot with anything operations or revenue critical. mimik changes that equation by turning Spot into a faster, more flexible and more intelligent compute fabric that spans your AWS estate and your endpoints.

The problem: Spot is inexpensive, but not operationally impactful or business-friendly

Spot is brilliant for cost savings, but it was never designed around your most important workloads. You get a two‑minute interruption notice; then it is your responsibility to scramble options. Either pre-warm capacity (resources) with the runtime stack – Docker, Kubernetes and VMware – otherwise it takes over 12 mins to start the stack – to maintain operational continuity so you can dynamically move your workload or restart the workload on another resource and begin the operation from scratch. The former is costly and inefficient, while the latter is cumbersome and unpredictable.  The result:

• Teams limit Spot to expendable batch jobs.
• Real-time and customer-facing services stay on more expensive, overprovisioned on‑demand capacity.

In an AI-first world where workloads are more dynamic, contextual, and latency-sensitive, this model simply does not scale.

Enter mim OE: a lightweight Spot fabric

mimik’s operating and execution environment, mim OE, is a lightweight microservice runtime and control plane that runs both on cloud, AWS (Spot and on‑demand), on-prem, gateways and on endpoint devices such as drones, cameras, smartphones, robots, and industrial PCs. Because the mim OE runtime is a serverless environment – negligible pre-warm overhead and sub‑second startup – you no longer need to keep “hot” VMs alive just in case a Spot interruption happens. Instead of managing VMs, you describe microservices and agents once, let mim OE dynamically move the service to another resource within even less than 2 minutes’ notice time and can also decide where they should run at any given moment, whether on a Spot instance, an on‑demand node, or an endpoint.

From “best-effort batch” to “near-continuous” Spot

Today, initializing the runtime stack can take 15 minutes or more, which is far beyond the two-minute Spot termination window. mim OE and its utility agents collapse that gap by:

• Keeping microservices pre-warmed in a lightweight runtime
• Automatically moving them between available worker resources when Spot capacity shifts
• Maintaining stable service addresses so callers never need to know which node is active

For your team, this feels like Spot with continuity. Workloads can dynamically move without operational interruptions, making Spot viable for real production services that are stateless and state-light – not just back-office batch jobs.

Extending Spot beyond the data center

The biggest shift mimik unlocks is conceptual: Spot no longer needs to stop at the boundary of your AWS region. With mim OE, compute no longer ends at your cloud boundary. Your endpoint devices become first-class participants in the same elastic pool as EC2 capacity, allowing compute-enabled devices such as gateways, PCs, mobile phones, drones, robots, etc. to execute microservices and agents locally for low-latency inference execution and filtering. When a task exceeds local, proximity and account-level compute capacity, mim OE can escalate it to EC2 Spot, NVIDIA GPUs, or private clouds automatically.

This “Spot everywhere” model reduces bandwidth costs, delivers energy efficiencies, sharpens user experience, and lets you treat AWS as the broker of a global device-first continuum of compute rather than just traditional centralized or on-prem cloud.

Direct business value for AWS enterprises

For enterprise leaders, this is not just an architecture story. It is a P&L story. Faster restart and smarter placement make it safer to move more workloads from on‑demand to Spot, without designing everything as expendable. You also reduce idle and energy costs by eliminating large pools of pre-warmed containers and VMs because mim OE’s lightweight runtime consumes very little energy even when services are standing by.

This creates new revenue and margin opportunities. Idle capacity on endpoints can be monetized through an AWS-managed marketplace, while AWS (or you, in a platform role) can capture brokerage value when workloads escalate to GPU clouds or other hyperscalers. mimik enables agentix-native AI workloads to run as parallel, context-aware microservices that collaborate across endpoints and Spot instances, rather than being trapped inside monolithic VM deployment cycles.

For many enterprises, this is the missing layer between today’s cloud architectures and the “continuum intelligence” vision enterprises desire to deliver.

What it takes to get there

There are practical considerations before you turn Spot into a global fabric:

• Architectural complexity: mim OE introduces a powerful but new control plane with a rich suite of utility agents for discovery, workload placement, and service coordination that must operate alongside existing AWS tools and Spot Fleets.
• Application refactoring: To fully benefit, workloads need to move towards microservice/agent patterns, externalizing state and tolerating mobility between devices and EC2(s).
• Security and governance: Running Spot-style workloads across cloud and endpoints demands strong identity, token management, encryption, and data placement controls. However, do not fret as mimik has all the tools to make these steps simple.

The upside is a Spot strategy that aligns with where your business is actually going, real-time, AI-driven, distributed, and margin-conscious.

Call to action

If your AWS team is under pressure to cut cloud spend without sacrificing SLAs, make AI workloads more responsive, or turn the devices you already own into part of your compute advantage, then it is time to look at how mimik and AWS Spot can work together. mim OE does not replace AWS Spot. It upgrades it, transforming “cheap spare capacity” into a distributed continuum of intelligence that spans your data centers, your edge, and everything in between. If you are interested in piloting this model in your AWS environment or simply want to explore what a Spot-powered continuum could look like for your architecture, reach out to the mimik team and start the conversation.

The post Make AWS Spot Instances Operationally Impactful for AI and Mission-Critical Workloads with mimik first appeared on mimik.

Today, many organizations struggle to roll out AI due to high infrastructure costs, compatibility issues, security concerns, and system fragmentation. mimik and Advantech aim to solve these challenges by combining their strengths: Advantech’s comprehensive range of Edge AI hardware and mimik’s agentix-native software systems for edge-based AI workflow automation.

At the heart of this collaboration is mimik’s “agentix-native” platform, which allows devices to automatically discover each other and work together without manual setup. Once connected, devices instantly become operational – no matter the hardware, operating system, or AI model in use. This allows businesses to run AI applications more flexibly, securely, and cost-effectively, without needing to rebuild their systems every time a new device or AI model is added.

“This partnership brings together the best of both worlds – mimik’s agentic AI software and Advantech’s comprehensive Edge AI platform,” said Linda Tsai, President of the Intelligent System Sector at Advantech. “It empowers our customers to roll out smart, secure, and collaborative Edge AI systems in sectors like manufacturing, transportation, healthcare, and defense – without limitations.”

“Dynamic discoverability with built-in zero-trust security is not a feature, it’s the strategic foundation for collaborative autonomy,” said Fay Arjomandi, Founder and CEO of mimik. “This partnership transforms what might otherwise appear as a fragmented array of hardware, ranging from cameras and drones to industrial gateways, rugged PCs, and hyperscaler systems, into a unified, adaptive compute continuum. With mimik’s dynamic discovery and runtime software layered across this spectrum, enterprises can choreograph agentic workloads on the fly, without being locked into any single model or compute provider. It’s not just a more flexible AI deployment model; it’s a smarter business model. That’s the promise of mimik: YOUR ROI FOR AI.”

About mimik

mimik powers the Agentic Economy with Agentix-Native software that turns everyday devices into intelligent collaborative systems. Its software platform enables real-time inference across smartphones, cameras, drones, robots, machines, and servers. By creating a Device-First AI continuum across endpoint devices and the cloud, mimik gives way to enterprises to operationalize agentic AI, scale intelligence, and optimize performance and cost. For more info visit https://mimik.com/

mimik Contact:

PR@mimik.com

About Advantech:

Advantech’s corporate vision is to enable an intelligent planet. The company is a global leader in the fields of IoT intelligent systems and embedded platforms. To embrace the trends of IoT, big data, and artificial intelligence, Advantech promotes IoT hardware and software solutions with the Edge Intelligence WISE-PaaS core to assist business partners and clients in connecting their industrial chains. Advantech is also working with business partners to co-create business ecosystems that accelerate the goal of industrial intelligence. (www.advantech.com)

Advantech Contact:

Alyse.Ho@advantech.com.tw

Tel: +886-2-2792-7818, Ext. 1236

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The center is a Physical AI production-first environment that trains, certifies, and supports developers and enterprises in building agentic-native workflows. These workflows mimic real-world business operations and execute autonomously across devices. Empowered with the right tools, developers and enterprises will be able to easily operationalize Agentic Native AI solutions.

The partnership will combine mimik’s Device-First Continuum AI Execution Fabric with Tech Mahindra’s deep engineering expertise in end compute systems and devices stack across industries such as automotive, communications, industrial, etc. This combination will enable quick and seamless introduction and integration of new features for OEMs, leveraging AI agents that operate with real-time, context-aware intelligence across a wide range of end compute stacks, including SDVs, smartphones, drones, robots, and industrial sensors. These agents are designed to function offline first, without constant connectivity to the cloud, while remaining capable of using any cloud service when needed.

“This is where physical AI becomes real,” said Fay Arjomandi, Founder and CEO of mimik. “We’re helping enterprises move beyond prototypes and dashboards to deploy AI agents that work autonomously on the entire continuum compute fabric, including across everyday devices like smartphones, drones, and robots, mirroring real-world processes and to any cloud as needed, unlocking real economic value.”

Narasimham RV, President – Engineering Services, Tech Mahindra, said, “As organizations push product and operational boundaries, the need for real-world, autonomous AI systems is more critical than ever. Our partnership with mimik to launch the Agentic AI Production Center is a significant step towards enabling hypercognition and rapid innovation at the edge, maximizing the potential of physical-digital interplay. This opens pivotal opportunities for organizations to evolve products faster and stay ahead in their transformation journey.”

The partnership reflects Tech Mahindra’s promise of Scale at Speed™ with a platform-led, AI-driven approach to product engineering. The Agentic Economy is here, providing reach and acceleration into areas that weren’t possible earlier, auguring a new movement in product innovation.

About mimik

mimik powers the Agentic Economy with Agentix-Native software that turns everyday devices into intelligent collaborative systems. Its software platform enables real-time inference across smartphones, cameras, drones, robots, machines, and servers. By creating a Device-First AI continuum across endpoint devices and the cloud, mimik gives way to enterprises to operationalize agentic AI, scale intelligence, and optimize performance and cost. For more information on how mimik can Partner with you, please visit: https://mimik.com

About Tech Mahindra

Tech Mahindra (NSE: TECHM) offers technology consulting and digital solutions to global enterprises across industries, enabling transformative scale at unparalleled speed. With 150,000+ professionals across 90+ countries helping 1100+ clients, Tech Mahindra provides a full spectrum of services including consulting, information technology, enterprise applications, business process services, engineering services, network services, customer experience & design, AI & analytics, and cloud & infrastructure services. It is the first Indian company in the world to have been awarded the Sustainable Markets Initiative’s Terra Carta Seal, which recognizes global companies that are actively leading the charge to create a climate and nature-positive future. Tech Mahindra is part of the Mahindra Group, founded in 1945, one of the largest and most admired multinational federation of companies. For more information on how TechM can partner with you to meet your Scale at Speed™ imperatives, please visit https://www.techmahindra.com

Contacts

Press Contact:
PR@mimik.com

Press Contact:
media.relations@techmahindra.com

https://www.businesswire.com/news/home/20250630917270/en/mimik-and-Tech-Mahindra-Unveil-a-Pioneering-Agentic-AI-Production-Center

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With mimik’s platform pre-integrated across AMD-based systems, enterprises and developers can achieve out-of-the-box agentic deployment today, with the certainty to deliver intelligence wherever it’s needed in the business to drive rapid growth. The result is a context-aware, dynamically discoverable, adaptive, and resilient compute fabric, with built-in zero-trust security, network offline-first capability, and seamless multi-cloud integration when agentic AI requires it. Developers can start building and deploying agentic workflows immediately, accelerating solution delivery without needing to rebuild infrastructure.

“This collaboration marks a turning point,” said Fay Arjomandi, Founder and CEO of mimik. “We’re not retrofitting legacy AI. We’re enabling, giving developers and enterprises a frictionless way to adopt and scale agentic AI where compute is fluid, intelligence is choreographed, and AI execution is embedded into every layer of infrastructure. With this integration, AMD hardware becomes an execution-ready environment for real-time AI, optimized for business-critical workloads across diverse environments.

AMD shares this vision of an adaptive, agent-ready future. “Our collaboration with mimik enables a new generation of AI systems that are responsive, distributed, and production-ready,” said Ramine Roane, corporate vice president, Artificial Intelligence Group, AMD. “By embedding mimik’s execution environment across AMD platforms, from the smallest cameras and robots to the largest server, we’re enabling real-time AI that’s dynamic, sovereign, and built for scale. This is the future of AI compute: ubiquitous, intelligent, enterprise and developer ready.”

mimik’s software enablers, pre-integrated across AMD platforms and built on an open API model, allow developers and enterprises to deploy agentic workflows out-of-the-box, locally or in coordination with other nodes. The result is a dynamically choreographed mesh of AI agents operating across AMD’s device-first continuum compute fabric that is context-aware, resilient, offline-first, and cloud-capable when needed. This is the execution foundation of the Agentic Economy, ready to scale real-world impact, today.

Watch the demo video to see how mimik with AMD deliver Physical AI across the device-first continuum:

About mimik:
mimik powers the Agentic Economy with Agentix-Native software that turns everyday devices into intelligent collaborative systems. Its software platform enables real-time inference across smartphones, cameras, drones, robots, machines, and servers. By creating a Device-First AI continuum across endpoint devices and the cloud, mimik gives way to enterprises to operationalize agentic AI, scale intelligence, and optimize performance and cost.

Press Contact:
PR@mimik.com

AMD, the AMD Arrow Logo, AMD Instinct, ROCm, and combinations thereof are trademarks of Advanced Micro Devices, Inc. Other names are for informational purposes only and may be trademarks of their respective owners.

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Built on SAT’s expertise in fatigue prediction and prevention, the FaaS platform leverages mimik’s DFC-AI to provide real-time, privacy-first fatigue insights without relying on always-on cloud connectivity. This ensures universal compliance with regional regulations, removes the burden of country-specific customizations, and enables seamless global scalability.

“SAT has spent years perfecting fatigue management solutions that help organizations proactively address one of the most critical safety risks,” said Riccardo Groppo, CEO of Sleep Advice Technologies. “By integrating our product with mimik’s AI enablers, we’re delivering a first-of-its-kind solution that empowers businesses to prevent fatigue-related risks before they occur.”

mimik’s DFC-AI, built on its DF-HEC platform, shifts AI processing to endpoint devices, transforming them into autonomous, AI-powered nodes that detect fatigue risks in real time, even in remote, high-risk, and low-connectivity environments. The two companies are also working on embedding SAT’s fatigue intelligence into mimik’s HybridTrax solution. The partnership sets a new industry benchmark for safety and productivity across transportation, maritime, logistics, construction, and industrial operations.

“This partnership is a game-changer for workforce safety,” said Fay Arjomandi, Founder and CEO at mimik. “By combining SAT’s fatigue expertise with our DFC-AI technology, we’re helping organizations eliminate risks before they become incidents and increase productivity.”

To see the demo at NVIDIA GTC 2025, Book a meeting: https://www.mimik.com/our-events/live-demo-ai-agents-in-action-gtc-booth-3117/

To learn more, visit: SAT and  mimik.ai, and for developers, developer.mimik.com.

About SAT

SAT reduces fatigue-related worker injuries and accidents through real-time interpretation of physiological parameters, tracking fatigues, and by predicting sleep occurrences using proprietary, medically-proven, AI-driven approaches. SAT relies on 240 years of cumulated know-how in sleep medicine, neurology, automotive, biomedical engineering, semiconductor technology, and embedded software.

Contact

info.sat@satechnologies.eu

About mimik

mimik is for Agentix Native, the 5th Element of AI. We have solved the most complex challenges in AI software, including AI Continuum on Continuum Compute, Parallel AI, and the Network Offline-First Distributed Dynamic Agentic Service Mesh Problem. Our technology enables seamless, scalable, and efficient agentic workflows, automation, and autonomous decision-making across all compute layers.

By accelerating AI adoption and enabling intelligent workflow operations, mimik ensures enterprises maintain full control, security, and efficiency. With Zero-Trust Security and optimized operational efficiency in both energy and cost, businesses can scale AI while staying resilient and adaptable in an ever-evolving digital landscape. mimik, Your ROI for AI.

Contact

PR@mimik.ai

https://www.businesswire.com/news/home/20250320011244/en/Sleep-Advice-Technologies-and-mimik-Partner-to-Revolutionize-Driver-and-Crew-Safety-with-Intelligent-Fatigue-as-a-Service

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This partnership sets a new standard for edge-enabled AI in smart spaces.

The Centific-mimik solution pioneers an adaptive compute continuum, dynamically distributing AI workloads across edge devices, servers, and private cloud environments based on operational needs. This edge-first strategy eliminates cloud latency, reduces bandwidth overhead, and helps ensure AI-driven insights are context-aware, responsive, and secure within an organization’s operational framework.

By leveraging mimik’s scalable Open Edge (OE) platform alongside Centific’s Frontier AI data foundry platform, the solution enables:

1. Federated AI processing across thousands of cameras with minimized data movement, optimizing edge execution.

2. Hybrid cloud integration to balance real-time decision-making at the edge with deeper analytics in secure cloud environments.

3. Autonomous AI agents leveraging multimodal video-linguistic AI models to provide proactive situational awareness.

 4. Event-driven intelligence that enhances security and operational efficiency without dependency on constant connectivity.

Centific’s Frontier AI data foundry platform elevates edge AI capabilities

Centific’s Frontier AI data foundry platform plays a critical role in optimizing AI-driven video intelligence by:

• Supporting 100s of use cases across industries with adaptable AI workflows and multi-model processing.
• Leveraging 100+ pre-configured templates for rapid and efficient data extraction, localization, and contextualization.
• Addressing data scarcity and privacy concerns by generating realistic synthetic datasets.
• Helping to ensure data integrity with AI-driven validation and human-in-the- loop (HITL) oversight in quality assurance processes.
• Enforcing safe AI practices with data privacy and compliance mechanisms on a global scale.
• Providing enterprise-ready AI models that maximize performance and minimize costs through advancements in LLM fine-tuning and model optimization.

Centific’s Frontier AI data foundry platform integrates seamlessly with mimik’s edge intelligence platform, helping to ensure that AI models remain contextually adaptive, continuously refined, and efficiently deployed across diverse environments.

“At Centific,” said Venkat Rangapuram, CEO of Centific, we are committed to harnessing AI to create safer communities by making AI-driven solutions more accessible and affordable across all devices. Our collaboration with mimik reinforces this vision, bringing edge intelligence and real-time AI analytics to the forefront of public safety. By leveraging our Frontier AI data foundry platform-driven approach, we can help ensure that AI is not only scalable and cost-effective but also privacy-conscious and contextually adaptive. This marks a new era where organizations can deploy intelligent security solutions with heightened situational awareness while reducing infrastructure costs. Together, we are making AI work for everyone, everywhere.”

“mimik’s DFC-AI is transforming enterprise AI deployments,” added Fay Arjomandi, Founder & CEO of mimik. “By harnessing the power of edge intelligence and federated AI, we enable organizations to execute agentic AI workloads efficiently, even in connectivity-limited environments.”

This partnership is the future of AI-powered smart spaces.

This partnership marks a pivotal shift in AI-driven security and public safety. By reducing reliance on cloud infrastructure and leveraging intelligent edge computing, organizations can now deploy scalable, privacy-conscious AI systems that operate with heightened situational awareness and reduced operational costs.

To see the demo at NVIDIA GTC 2025, Book a meeting: https://www.mimik.com/our-events/live-demo-ai-agents-in-action-gtc-booth-3117/

To learn more, visit: www.centific.com.

To learn more, visit: mimik.ai, and for developers, developer.mimik.com.

About Centific:

Centific lives at the forefront of AI innovation, specializing in platform-driven solutions that transform raw data into fuel for the future of AI. By elevating data quality and accelerating AI deployments, Centific empowers businesses to build smarter, safer, and more scalable AI solutions. The company’s commitment to collaboration spans academia, industry, and technology, with a focus on sustainable practices that address real-world needs.

Join Centific in redefining the AI landscape at www.centific.com and follow us on LinkedIn.

Centific contact:

Lee Gibbs

press@centific.com

About mimik:

mimik is for Agentix Native, the 5th Element of AI. We have solved the most complex challenges in AI software, including AI Continuum on Continuum Compute, Parallel AI, and the Network Offline-First Distributed Dynamic Agentic Service Mesh Problem. Our technology enables seamless, scalable, and efficient agentic workflows, automation, and autonomous decision-making across all compute layers.

By accelerating AI adoption and enabling intelligent workflow operations, mimik ensures enterprises maintain full control, security, and efficiency. With Zero-Trust Security and optimized operational efficiency in both energy and cost, businesses can scale AI while staying resilient and adaptable in an ever-evolving digital landscape. mimik, Your ROI for AI.

mimik contact:

PR@mimik.ai  

https://www.businesswire.com/news/home/20250319791637/en/Centific-and-mimik-Partner-to-Revolutionize-AI-powered-Smart-Spaces-With-Edge-Intelligence

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